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A Toolbox for Adversarial Robustness Research
This is the code of the paper "Orthogonal-Coding Based Feature Generation for Transductive Open-Set Recognition via Dual-Space Consistent Sampling", which is submitted to Journal for review and the arXiv version is available on https://arxiv.org/pdf/2207.05957.pdf. The authors are Jiayin Sun and Qiulei Dong.
make pairs for face verification
This is the code for the paper "MoEP-AE: Autoencoding Mixtures of Exponential Power Distributions for Open-Set Recognition", which is under review. The authors are Jiayin Sun, Hong Wang, and Qiulei Dong.
This is the code for the paper "MoEP-AE: Autoencoding Mixtures of Exponential Power Distributions for Open-Set Recognition", which is under review. The authors are Jiayin Sun, Hong Wang, and Qiulei Dong. Environments: Python 3.7.7, Pytorch 1.7.1, CUDA 10.1.105, GPU NVIDIA TITAN X To train: python train_MoEP_AE_macro_F1_scores.py To test: python eval_MoEP_AE_macro_F1_scores.py
This is the code for our paper: "Spatial-Temporal Attention Network for Open-Set Fine-Grained Image Recognition", which is under review.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
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China tencent open source team.